Estimation of Stress-Strength Reliability for Quasi Lindley Distribution

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Amr Fouad Sadek
Mostafa Mohie El-Din
Shaimaa Elmeghawry


This paper discussed the problem of stress-strength reliability model R=Pr(Y< X). It is assumed that the strength of a system X, and the environmental stress applied on it Y, follow the Quasi Lindley Distribution(QLD). Stress-strength reliability is studied using the maximum likelihood, and Bayes estimations. Asymptotic confidence interval for reliability is obtained. Bayesian estimations were proposed using two different methods: Importance Sampling technique, and MCMC technique via Metropolis-Hastings algorithm, under symmetric loss function (squared error) and  asymmetric loss functions (linex, general entropy). The behaviors of the maximum likelihood and Bayes estimators of stress-strength reliability have been studied through the Monte Carlo simulation study. 


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How to Cite
Sadek, A., Mohie El-Din, M., & Elmeghawry, S. (2018). Estimation of Stress-Strength Reliability for Quasi Lindley Distribution. Advances in Systems Science and Applications, 18(4), 39-51.
Author Biographies

Mostafa Mohie El-Din, Al-Azhar University

Dep. of Mathematics, Faculty of Science, Al-Azhar University, Egypt

Shaimaa Elmeghawry

Faculty of Engineering, Benha University, Egypt